Phenotypic data of nitrogen use efficiency related traits and genotypic data of BGEM lines

These data set (phenotypic and genotypic data) can be used in the genetics and plant breeding area. Currently, many projects have been using analyzes that associate the phenotype of interest with the genotype. Thus, it allows identifying possible regions of the genome that have the greatest effect on the trait. Our data comprise 181 doubled haploid (DH) lines derived from crosses between landraces from the Germplasm Enhancement of Maize (BGEM lines) project and two inbreds, PHB47 and PHZ51. These DH lines were genotyped using 62,077 molecular markers (single nucleotide polymorphisms - SNPs) using genotyping-by-sequencing (GBS). The same lines from the per se trials were used as parental lines for the testcross field trials. Plant height (PHT, cm), days to female flowering (SLK, days), days to male flowering (ANT, days), anthesis to silking interval (ASI), and grain yield (YLD, tons per hectare) were collected from high (HN) and low N (LN) conditions in two environments for testcrosses (Ames 2015B, Nashua 2015) and three environments for per se trials (Ames 2014, Ames 2015 and Nashua 2015). Our data might be used for Genome Wide Association Studies (GWAS) and Selection (GWS). Furthermore, molecular characterization and genetic diversity might be performed.

本数据集包含表型与基因型数据，可应用于遗传学与植物育种研究领域。当前诸多科研项目均采用关联目标表型与基因型的分析方法，借此可识别出对目标性状影响最为显著的基因组区域。本数据集包含181个双单倍体（doubled haploid, DH）系，这些DH系由玉米种质改良（Germplasm Enhancement of Maize, BGEM）项目中的地方品种与两个自交系PHB47、PHZ51杂交获得。这些DH系通过测序分型（genotyping-by-sequencing, GBS）技术，利用62077个单核苷酸多态性（single nucleotide polymorphisms, SNPs）分子标记完成了基因型鉴定。源自纯系本身试验（per se trials）的同一套DH系，被用作测交田间试验的亲本材料。本研究采集了以下5项农艺性状数据：株高（Plant height, PHT，单位：厘米）、雌穗开花天数（days to female flowering, SLK，单位：天）、雄穗开花天数（days to male flowering, ANT，单位：天）、散粉-吐丝间隔期（anthesis to silking interval, ASI）以及籽粒产量（grain yield, YLD，单位：吨/公顷）。上述性状的采集覆盖两类试验：测交试验设置2个环境（Ames 2015B、Nashua 2015），分别在高氮（high nitrogen, HN）与低氮（low nitrogen, LN）两种氮素水平下开展；纯系本身试验设置3个环境（Ames 2014、Ames 2015、Nashua 2015），同步采集上述性状数据。本数据集可用于全基因组关联分析（Genome Wide Association Studies, GWAS）与基因组选择（Genome Wide Selection, GWS）研究，此外还可开展分子特征解析与遗传多样性分析相关工作。